Investigating Iraqi EFL Learners’ Social Intelligence and Their Performance in Speaking: A Correlational Study

	Al-Noor Journal for Humanities
	https://jnh.alnoor.edu.iq/
Investigating Iraqi EFL Learners’ Social Intelligence and Their Performance in Speaking: A Correlational Study   M A Ohmayed  and S S Abdulfattah   Department of  Translation, College of Arts, University of Mosul, Iraq
Article information			Abstract
Article history: Received 18 May, 2024 Revised: 20 June, 2024 Accepted 24 June, 2024			The ultimate goal of learning a language is to use it when interacting with others regardless of the mode of communication. This use of the language, however, is socially and psychologically affected. In this regard, social intelligence plays a crucial role in creating effective interactions. The problem is that the correlation between social intelligence and speaking skill has received little attention in the field of linguistics concerning the Iraqi context. Therefore, this study aims to investigate the correlation between these variables to better understand how they correlate to each other. It asks to what extent there is a correlation between them and whether some personal variables affect this correlation. To this end, the alternative hypothesis is adopted which claims that there is a statistically significant positive correlation among the variables. For this purpose, the correlation design that draws on the quantitative approach is adopted. Moreover, a sample of 77 EFL third-year students from the University of Mosul for the academic year 2023-2024 was randomly selected. They were males and females coming from ethnic backgrounds, namely, Arabs, Kurds, and Turkmen. To collect data, two research instruments were used they were: an adopted and adapted social intelligence scale and a speaking test designed by the researcher. The data were statistically treated by a statistician using SPSS.  The results of the study show that there is a positive moderate correlation between social intelligence and speaking skill. It is also concluded that personal variables such as gender and ethnicity have no significant influence on the correlation between the variables. Finally, some recommendations were presented based on the conclusions inferred
Keywords: Social Intelligence, Speaking Skill, Social Awareness, Correlational Study
Correspondence: Meaad Abbas Ohmayed [email protected]
DOI: https://doi.org/10.69513/jnfh.v2.i3.a6 ©Authors, 2024, College of Education, Alnoor University. This is an open access article under the CC BY 4.0 license (http://creativecommons.org/licenses/by/4.0/).

 

 

دراسة الذكاء الاجتماعي لمتعلمي اللغة الإنجليزية كلغة أجنبية في العراق وأدائهم في التكلم: دراسة ارتباطية

 

ميعاد عباس احميد      و شعيب سعيد عبد الفتاح

 

قسم اللغة الانكليزية، كلية التربية الانسانية، جامعة الموصل، العراق

 

ملخص البحث:

الهدف النهائي لتعلم اللغة هو استخدامها عند التفاعل مع الآخرين بغض النظر عن وسيلة التواصل. غير أن هذا الاستخدام للغة يتأثر اجتماعيا ونفسيا. وفي هذا الصدد، يلعب الذكاء الاجتماعي دورًا حاسمًا في خلق تفاعلات فعالة. المشكلة هي أن العلاقة الارتباطية بين الذكاء الاجتماعي ومهارة التحدث لم تحظ باهتمام كبير في مجال اللغويات المتعلقة بالسياق العراقي. ولذلك، تهدف هذه الدراسة إلى دراسة الارتباط بين هذه المتغيرات لفهم كيفية ارتباطها ببعضها البعض بشكل أفضل. وتتساءل عن مدى وجود علاقة ارتباط بينهما وهل تؤثر بعض المتغيرات الشخصية على هذا الارتباط. ولهذا الغرض تم اعتماد الفرضية البديلة التي تقول بوجود علاقة ارتباط إيجابية ذات دلالة إحصائية بين المتغيرات. ولتحقيق هذه الغاية، تم اعتماد تصميم الارتباط الذي يعتمد على المنهج الكمي. كما تم اختيار عينة عشوائية مكونة من 77 طالباً من طلاب السنة الثالثة في جامعة الموصل للعام الدراسي 2023-2024. وكانوا ذكوراً وإناثاً ينحدرون من خلفيات عرقية، وهي العرب والأكراد والتركمان. ولجمع البيانات تم استخدام أداتين للبحث هما مقياس الذكاء الاجتماعي المتبنى والمكيف، واختبار المحادثة الذي صممه الباحث. وتمت معالجة البيانات إحصائيا من قبل الإحصائي باستخدام برنامج SPSS. وأظهرت نتائج الدراسة وجود علاقة ارتباطية موجبة متوسطة بين الذكاء الاجتماعي ومهارة التحدث. كما خلصت إلى أن المتغيرات الشخصية مثل الجنس والعرق ليس لها تأثير كبير على العلاقة الارتباطية بين المتغيرات. وأخيرا، بعض التوصيات تم تقديمها بناء على الاستنتاجات التي تم التوصل إليها.

الكلمات المفتاحية: الذكاء الاجتماعي, مهارة التكلم, الوعي الاجتماعي، دراسة ارتباطية

 

 

1. 1. Introduction

1.1Statement of the problem

    The problem addressed in the present study is that the correlation between Social Intelligence (SI) and other variables has primarily been studied psychologically and only few studies relate it to linguistic issues such as speaking. Therefore, this study attempts to assess the correlation between SI and speaking skill and relate them to linguistic issues rather than purely psychological ones as studied in the Iraqi context.

1.2 Questions of the Study            

   The study raises the following questions:

1.What is the level of Iraqi EFL university students’ social intelligence, and performance in speaking skill?

2.To what extent is there a correlation between EFL university students’ social intelligence and their performance in speaking skill?

3.Do personal variables like gender and ethnicity have any influence on the strength of the association among Iraqi EFL university students’ social intelligence and performance in speaking skill?

 1.3 Aims of the Study

The study aims to:

1.Find out the level of Iraqi EFL university students’ social intelligence and their performance in speaking skills.

2.Find out the extent of the correlation between Iraqi EFL university students’ performance in speaking skills and their social intelligence.

3.Find out whether personal variables, particularly gender and ethnicity, impact the strength of the correlation between the study variables.

1.4 Hypotheses of the study

It is to be mentioned that the Alternative Hypothesis, which assumes that there is a statistically significant correlation among the variables, is adopted in this study. Therefore, in light of the aims set above, it is hypothesized that:

1.There is a statistically significant difference between the Iraqi EFL learners’ calculated mean score in a. SI, and b. speaking skill, and the hypothetical mean score.

2.There is a moderate positive correlation between SI and speaking skill.

3.There is a statistically significant difference in the correlation between SI and speaking skill according to the personal variables (gender and ethnicity).

1.5 Limits of the study

This study is limited to:

EFL third-year students in the University of Mosul/ Colleges of Education for Humanities/ Department of English Language/ morning study for the academic year 2023/2024. It is also restricted to one type of intelligence among many other types. Moreover, the study is limited to studying the association of SI and speaking only regardless of writing as a productive skill. 

2. 2. Literature Review

2.1 The Concept and Definitions of Social Intelligence                 

    Throughout reviewing the relevant literature, it appears that psychologists and sociologists have long debated the concept of social intelligence (henceforth SI). Prominent psychologists, including Thorndike, Moss and Hunt, Vernon, and Gardner, have discussed this topic. Dewey (1909) (1) and Lull (1911) (2) coined the term “social intelligence,” although the present definition dates back to Thorndike’s (1920)  (3) distinction between three forms of intelligence: abstract, mechanical, and social. Mechanical intelligence is concerned with physical objects, whereas abstract intelligence pertains to an individual’s capacity to comprehend and control concepts. In contrast, SI is concerned with a person’s ability to understand the others with whom they interact (3, 4), broadened his definition of SI to include the “ability to understand and manage men and women, boys and girls to act wisely in human relations”. Thorndike’s definition of SI identified two components: cognitive “understanding other people” and behavioral “to act wisely in human relations.” Thorndike’s definition is regarded as the primary and widely held definition of SI. Many additional definitions have been developed from it, particularly his distinction between cognitive and behavioural components. Thus, Vernon (5) defines SI as “knowledge of social matters and insight into the mood and personality trait of strangers” (cognition). As the ability to “get along with others and ease in society” (behavioral).”  Moss & Hunt ( 6)   define it as “the ability to get along with others” and “ability to judge people with respect to feelings, motives, thoughts, intentions, attitudes, etc.” Other definitions focus either on cognitive or behavioral aspects. Cognitively, for example, Dewey ( 1) states that SI is “the power of observing and comprehending social situations.”  In the same sense, Kihlstrom and Cantor (2000) explain that SI “involves a tendency to anticipate another’s response across a broad range of circumstances and sources.” Moreover, O’Sullivan et al., (7) describe SI as “individual’s fund of knowledge about the social world.       

     However, Gardener (1993) (8), in his theory of Multiple Intelligence, viewed SI as a broad concept that he referred to as interpersonal intelligence; he defines interpersonal intelligence as the ability of a person to observe distinctions among other’s intentions, motivations, desires, and moods of others. Seligman (2002) (9) illustrate that SI is the capacity of a person to observe “differences among others, especially with respect to their moods, temperament, motivation, and intentions, and then act upon these distinctions.” For him, SI is “good human relationships.” Albrecht (2006), (10) proposes that SI is a certain kind of strategic social awareness, social understanding, and a set of techniques and social skills for interacting with people successfully. He defines SI as “the ability to get along with others and to get them to cooperate with you.” To conclude, SI is defined differently based on how scholars view it. Some consider it a cognitive psychological construct, while others regard it as a behavioural construct. However, SI covers both aspects, cognitive and behavioural, because the cognitive competence of social intelligence is best mirrored in one’s behavior.

2.2 Key Elements of Social Intelligence

   Prabhu (2021), (11) mentions the key elements of SI as follows:                                                                                 

1. 1. Verbal fluency and conversational skills: A highly socially intelligent person is prominent in social gatherings because they know how to ‘work the room’. He is tactful and can carry on conversations with diverse people.

2 Knowledge of social roles, rules, and scripts: Socially intelligent individuals know how to play various social roles and are aware of informal roles and norms.                                                                             

3. 3. Effective listening skills: As a great listener, a socially intelligent person can maintain good connections with others.
4. 4. Understanding what makes other people tick: As a great observer, an individual high in social intelligence reads what others say and behaves to understand others. Similarly, Buzan (2002, p. 5) states, “socially intelligent person is a superb conversationalist and listener, able to relate successfully to the wide world.
5. 5. Social self-efficacy: As a role-playing taker, a socially intelligent person feels comfortable and socially self-confident.
6. 6. Impression management skills: An individual with social intelligence is concerned with the impression he makes on others. In Prabhu's (2021,(11) words, “he engages in the dangerous art of impression management.” It is a sensitive balance between managing and controlling the impression the person portrays to others and being reasonably “authentic.” In many situations, the messages are sent via postures, movements, facial expressions, gestures, and tone of voice. The person can make an impression through his physical appearance, body language, and the space he occupies in the room.

2.3 Measuring Social Intelligence

 It appears to be relatively simple to define social intelligence, particularly when compared to abstract intelligence. In contrast, concerning the assessment of social intelligence, Thorndike (1920), (3) acknowledges the difficulty in creating practical tests of SI. Social intelligence is readily observed in many settings such as nurseries, playgrounds, barracks, workshops, and salesrooms. However, measuring under controlled conditions in a testing laboratory proves difficult. It requires human beings to respond to, time to adapt its responses, and face, voice, and gesture as tools. However, in accordance with the objectives of the psychometric standards, researchers promptly transformed abstract notions of social intelligence into standardized laboratory tools for assessing variations in social intelligence among individuals (12,13). There are many assessment scales for measuring social intelligence. The common and standardized measurements are as follows:

2.3.1 The George Washington Social Intelligence Scale

The George Washington Social Intelligence Test (GWSIT) was among the earliest SI tests of SI (13). The GWSIT was first established in 1928 at its namesake institution and was based on Thorndike’s original multidimensional concept of SI; SI is “…the ability to understand and manage men and women… to act wisely in human relations (12).” Furthermore, the publication of the GWSIT in the Journal of Applied Psychology was a turning point because it was the first method devised and made available that claimed to measure SI. In its original form, the GWSIT comprised six sections or subtests. They were (a) judgment in social situations, (b) memory of names and faces, (c) recognition of mental states from facial expressions, (d) observation of human behaviour, (e) social information, and (f) recognition of mental states behind words (ibid). Later editions of the test reduced these to five scales to make the test easier and faster to administer. The “facial expression” and “social information” sections were removed from the subsequent edition, while the “sense of humour” subtest was included (14,15). Nevertheless, the GWSIT faced early criticism due to its significant association with abstract intelligence. According to Thorndike and Stein (1937)(3), the GWSIT is strongly influenced by the ability to use language and concepts. As a result, variations in social intelligence are overshadowed by variations in abstract intelligence.   

2.3.2 Six-Factor Tests of Social Intelligence

Guilford’s group formulated the Six Factor Test of Social Intelligence. It was initially released in 1966 and revised ten years later to become the Four Factor Test. The assessments were founded upon Guilford’s “Structure of Intellect” framework concerning human intelligence (15). A concise overview of the six factors (13) is listed below:

(a) Cartoon Predictions: This test aims to select one of three alternative cartoons that depict what is most likely to happen in a specific interpersonal situation cartoon series. This cognition is the ability to draw implications or make predictions about what will happen following a given social situation.

(b) Expression Grouping: Each question in this test consists of a set of three drawings representing face expressions, hand gestures, or body positions. The objective is to indicate comprehension of the class of the initial three expressions by selecting one of the four alternative illustrations. Understanding the similarity between behavioural information expressed in various modalities of expression constitutes this cognitive ability 

(c) Missing Cartoons: The objective is to determine which of four cartoons most effectively illustrates a missing element in a complete sequence. Missing Cartoons is a reasonably significant indicator of behavioral system cognition and organizational ability.                                                            

(d) Missing Pictures: The stimuli for this exam are a series of images of college students acting out a sequence of events, with the entire set conveying a story if the student selects the correct picture to complete the indicated sequence for behavioral system cognition.                                                  

(e) Picture Exchange: For this assignment, the student is required to select a photograph and replace it with one of four marked alternatives in a way that alters the meaning of the given story for the comprehension of behavioral alterations     

(f) Social Translations: This subtest is the sole verbal indicator of social intelligence. The objective is to determine which of three possible pairs of individuals shares a distinct meaning when exchanging a verbal statement dissimilar from that which would be exchanged between individuals of a distinct pair and cognition of behavioral modifications.

2.3.3 Tromsø Social Intelligence Scale (2001)

Silvera, et al., (2001), (16) established the Tromsø Social Intelligence Scale (TSIS). As part of their preliminary validation study, the authors interviewed fourteen psychology faculty members to develop the working definition of social intelligence as follows: “the capacity to comprehend the reactions of others in various social situations (16).” This definition was the foundation of their measuring the SI construct. The TSIS aims to propose an SI measurement design that considers the multidimensional nature of SI. The developers of the TSIS recognize both cognitive (“ability to understand others…”) and behavioral (“how they will react…”) aspects of social intelligence. The TSIS comprises three SI subscales and is administered as a self-report instrument. The subscales are: a) social information processing, b) social skills, and c) social awareness (ibid).

2.3.4 Chadda & Ganeshans’ Social Intelligence Scale (1986)

The dimensions in this scale used to measure SI were chosen based on the opinions of 25 behavioral science specialists. The initial version of the scale contained sixteen dimensions of SI. However, the scale was given to 25 experts, and they all agreed upon thirteen dimensions. Nevertheless, these dimensions were given to a further ten experts to rate them on five points rating scale of validity. Consequently, only eight dimensions were selected as the most relevant and representing the construct of SI. These dimensions were operationally defined by the developer of the scale as follows:                                                       

A.Patience: Maintaining calm under challenging conditions       

B.Cooperativeness: Ability to communicate with others pleasantly to see things from all aspects.                                            

C.Confidence Level: A firm belief in oneself and one’s chances      

1. Sensitivity: To be intensely attentive and receptive to human behavior.
2. Recognition of Social Environment: Perception of the current situation and its atmosphere.

F.Tactfulness: Delicate perception of what is appropriate to say or do.     

G.Sense of Humour: The ability to feel and make people laugh; the capacity to appreciate the positive aspects of life.

1. Memory: The ability to recall all relevant concerns and people’s names and faces (17). It is worth mentioning that the GWSIS measurement and six-factor test mainly measure the cognitive ability to understand others, while TSIS and SIS measure both the cognitive ability to comprehend social situations and the behavioural ability to act in social contexts.

2.4 Some Definitions of Speaking   

Speaking “is the expression of ideas and thoughts using articulate sounds produced by the vocal organs

 (18).” According to Chaney (1998, (19), speaking “is the process of building and sharing meaning through the use of verbal and non–verbal symbols in various contexts.” Speaking “is to express or communicate opinions, feelings, ideas, etc., by or as talking and it involves the activities on the part of speakers as psychological, physiological (articulator) and physical (acoustic) stage” (20). Speaking is “a skill which enables us to produce utterances, when genuinely communicatively, speaking is desire and purpose-driven, in other words, we genuinely want to communicate something to achieve a particular end

(21).” Speaking competence demands as much attention as literary skill in first and second languages. Language students must communicate confidently

(22).

2.5 Characteristics of Effective Speaking Proficiency             

 Accuracy and fluency are criteria that characterise effective speaking. They are explained in the followings subsections                               

1. 1. Accuracy: According to Khanlarzadeh et al. (2016), (23), accuracy is “the dimension of clarity, appropriateness, validity of a particular message concerning the participants’ interlocutors and certain language standards”. Three components comprise accuracy:
2. a) Grammar: Nation (2011), (24) stated that spoken grammar differed from written grammar. As Ur (2011) (25) noted, spoken language has a variety of informal lexicon-grammatical chunks, uses abbreviations, and coordinates phrases instead of subordinates. It formalises linguistic structure investigation and demonstrates how words form meaningful sentences

 (26).

28. b) Vocabulary: Accuracy in language determines talk acceptability. Students often struggle to communicate due to a lack of vocabulary and incorrect usage of synonyms and antonyms. Therefore, they must be prepared to employ phrases and words Taghilou (2019), (27). A language’s words, comprised of a single phrase and pieces of many words that carry a certain meaning, are similar to how people speak (28.)
29. c) Pronunciation: Taghilou (2019), (27) notes that FL pronunciation is harder for native and non-native learners. Language learners must develop pronunciation overall. Levis (2006), (29) argued that countable pronunciation accuracy was more important than other issues for measuring spoken language
30. 2. Fluency: Lems (2006), (30) stated that proficient speech was teachers’ primary goal in teaching productive ability. It indicated total target language proficiency. Nation (2011), (24) defines fluency as the ability to express oneself without accuracy. states that “fluency involves the simplest use of what is known under normal time constraints” as a challenging perspective. He suggested four fluency-boosting conditions: a) Use additional encouragement or pressure. b) Fluency requires practice and repetition. c) Students should be better familiar with teachers’ vocabulary and d) grammar resources.

2.6 Assessing and Testing the Oral Performance

In most educational institutions teaching English as a second or foreign language, assessing students’ spoken performance is an important part of the evaluation process. O’Malley and Pierce (1996), (31) state that the “Oral language assessment aims to capture student’s ability to communicate for both basic communicative and academic purposes.” The most frequently employed spoken assessments, as stated by Thornbury (2005) (32), are as follows: 

1. Interviews: Interviews can be conducted in pairs or alone. They are easy to arrange but not the best way to assess conversational, casual speaking styles. One cannot ignore the interviewer’s influence, including their style of questioning. According to Baily (2020), (33), the oral proficiency interview comprises four general phases: warm-up, level check, probe, and wind-down. During the warm-up phase, an interviewer engages the candidate in a brief discourse to establish rapport. In doing so, the interviewers gain an overall understanding of the individual’s capabilities. Following this, they conduct a level check by establishing task type crucial at that particular level. When the examinee maintains performance at that level, the interviewers investigate by assigning the candidate tasks requiring an even higher proficiency level. When the examinee maintains proficiency at that elevated level, the interviewers proceed to ask probing questions at the subsequent elevated level, and so forth. Once the level of consistent performance of the test-taker has been ascertained, the wind-down phase initiates. During this phase, the test-taker is assigned tasks significantly below their capabilities to conclude the interview on a positive note (33).
2. Live monologues: A brief presentation or lecture is delivered by each student on a predetermined subject. This type of examination eliminates the evaluator effect. As opposed to interviews, where it is not always feasible to assess the speakers’ conversational abilities, the examination furnishes such evidence
3. Recorded monologues and dialogues: It causes less anxiety compared to live performances. Students may record their discourse on a specified subject for this test. Post-performance evaluation of recorded monologues or dialogues allows evaluators to establish a standardised and objective assessment framework
4. Role-plays: This type of test can be considered reliable if the objectives of the language lesson and the learner’s requirements are fulfilled. Thornbury and Slade (2006) (34) state that in role plays, learners can “explore the effects of different contextual factors—power relationships, setting, communicative purpose, etc.—on language (p. 265).” According to these authors, role plays offer speaking opportunities that closely resemble real-life communication.
5. Collaborative tasks and discussions: They resemble role-playing exercises, except the students take on the part of themselves. Using this examination, evaluators can assess students’ interpersonal skills and capacity to express their views (pp. 123-125). “Collaborative tasks, where learners interact in pairs or small groups … have the advantage that they reflect communicative methodology and hence are likely to have a positive effect on classroom practice (35).”

2.7 A Review of Previous Studies

Although SI is a psychological topic mainly studied in the field of psychology, it is found that some studies relate it to linguistics. This, in fact, is usual since applied linguistics is an interdisciplinary field that makes use of different fields of knowledge to better understand the use of language and work on solving language-related problems in such fields. It is found that many researchers have investigated SI, for example, Teama and Al-Badri (2018),  (36), Ahmed and Mohammad (2020), (37) and Iqbal (2023) (38). Teama and Al-Badri (2018) (36) studied the role of SI in teaching and learning. Additionally, a similar study has been carried out by Ahmed and Mohammad (2020), (37) to find out the association between SI and students’ performance in language skills. Sharing a similar objective, Iqbal (2023), (38) studied the correlation between SI and postgraduate students’ academic performance. In spite of sharing a similar objective, which is studying SI, these studies differ from each other in some aspects.  For instance, Teama and Al-Badri (2018), (36) use a questionnaire to show the role of SI in learning and teaching by providing descriptive statistical accounts. Ahmed and Mohammad (2020), (37)  use an SI scale and language tests of productive skills. Moreover, Iqbal (2023) (38)adopts mixed method research to study the correlation between SI and students’ academic performance. These studies also differ in being conducted in different geographical contexts and on different samples.

       Moreover, some other studies studied the association between SI and WTC. In this context, Ghalani and Pahlavani (2019) (39) studied the correlation between SI and WTC among Iranian learners. They included the gender variable to examine if it impacts this relationship. In line with Ghalani and Pahlavani (2019) (39), Al-qurashi (2022) (40) studied the correlation between SI and WTC concerning gender distinctions among Saudi university students. Both studies found a positive correlation between SI and WTC and gender distinction does not influence this correlation. However, they are contextually different.

       The above-mentioned studies differ from the current one in that they were conducted in different countries and on different samples. Moreover, they use different research tools than the ones used in this study. More importantly, these studies deal either with SI and other issues that may or may not be related to linguistic areas or SI as a psychological topic, that is, with other psychologically oriented topics. SI is a purely psychological factor that can influence learners’ speaking skill. Therefore, studying the correlation between these variables is important since neurological linguistic processes are psychologically and sociologically bounded when verbally executed. As a result, this study attempts to fill this gap and add to the existing body of literature concerned with SI, WTC and language productive skills. 

3. 3. Methodology

3.1 Population and Sample

The population of the current study includes all the EFL third-year students at the Department of English, College of Education, University of Mosul, for the academic year 2023-2024, morning study. The total number of the population is (270) undergraduate students. The reason behind choosing this specific stage is because they represent a relatively advanced level because they supposedly have achieved a good level of academic proficiency in the English language. Additionally, they are more socially mature. This is essential since the variables under study focus on social and linguistic features. Demographically, the EFL learners are approximately the same age (21-23), in the same academic year (2023-2024), and share same nationality, which is Iraqi. However, the population consists of both male and female students, with different ethnicities (Arab, Kurd, and Turkmen), different religions (Islam, Christianity, Yazidi), and different mother tongues.

The study uses more than two data collection tools. This means that it is difficult, for reasons of time and effort, to cover all the targeted population. Therefore, a sample of (77) students is randomly selected to represent the population. Sample homogeneity is also taken into account to control the effect of other (intervening) variables on the results of the study. Therefore, in this study, some learners are excluded based on the results of the information form. Only two variables are focused on, namely, gender and ethnicity. Other variables such as multilingualism, religion, previous contact with native speakers, repeaters, and those who have travelled to a foreign country are all excluded. This helps to reduce the threats to validity and reliability of the study results.

3.2 Research Methodology

This study aims to investigate the association between the variables using data collection tools that result in numerical data. Therefore, this needs the use of the quantitative approach to help analyze the statistical results. Creswell (1994) (41) defines quantitative research as a type of study that collects numerical data and analyzes it using mathematically based methods to explain phenomena in particular statistics. These methods are followed based on the nature of the study. Within this quantitative approach, the present study adopts the correlational design since it seeks to test the association or correlation between two variables: learners’ social intelligence and their performance in speaking skill.

3.3 Data Collection Instruments

The researcher, reviewing the literature, found that the Chadha and Ganeshans’ (1986) (17) scale of social intelligence is the most widely spread in studies that target university students. Consequently, it has been adopted and adapted to suit the study context. The scale consists of eight dimensions, with many items under each dimension. These dimensions are patience, cooperativeness, confidence, sensitivity, recognition of social environment, tactfulness, sense of humour, and memory. The first six dimensions (patience, cooperativeness, confidence, sensitivity, recognition of social environment, and sense of humour) were constructed as multiple-choice questions. However, tactfulness was constructed as yes\no items, and memory was constructed as recognition of people test. With regard to speaking tests, it is found that two types of tests can be used. The first one is a self-assessment test of oral proficiency and an oral interview test. In this study, the researcher found that the oral interview test is more reliable and authentic than a self-assessment one. Therefore, some speaking interview questions were set in light of the IELTS test website questions with some adjustments. The test is divided into two main sections. The first section is a warm introduction. It requires the subjects to answer questions about their name, age, choosing the department of English, and the field they prefer. This section is meant to reduce any possible tension the subjects may feel and to increase their comfort regarding the test atmosphere. The second section, on the other hand, consists of three sets of questions. Each set comprises many questions. These sets are about general topics such as the internet, sports, and reading. The questions were designed to increase the speaking time of the subjects and reduce that of the interviewer. A scale developed by Alahmed (2010) (41) was adopted to score the speaking test. This rating scale follows the analytical scoring.

3.4 Validity and Reliability of the Research Instruments

The data collection instruments, have been submitted to a jury of experts specialised in linguistics and applied linguistics and were kindly requested to evaluate the content and face validity of the instruments. The validation is necessary since the study context and the sample are different. Concerning the speaking test, no suggestions or recommendations were given. Moreover, two jury members commented on the length of the SIS, and another one suggested that some items are unsuitable for the study context. Their recommendations were taken into account and adjustments were made in light of the jury members’ feedback. Consequently, some items were left out from the SIS to reduce its length, and some words were replaced by easier ones or explained by synonyms in brackets.

To estimate the reliability of the instrument, they were piloted to a group of EFL learners of the population, but not of the study sample. Accordingly, the results of the pilot study were submitted to a statistician to estimate the reliability of the tools by running some statistical tests. The reliability of the SIS was calculated using the Alph Cronbach formula. The reliability coefficient of SIS is 0.81 which is an acceptable value. Concerning the speaking test, it is found that the method of inter-rater reliability is more convenient to perform since it is scored subjectively. Based on this assumption, 20 of the recordings were given to another rater to score them. Next, the scores of each rater were compared using Pearson Correlation to estimate the reliability of scoring. The correlation coefficient between the two raters is found to be 0.86, which is an acceptable indication of reliability. 

4. 4. Data Analysis

The Shapiro-Wilk test is used to determine the distribution of the data. Concerning this study, the statistician has run the aforementioned test of normality and found that data is normally distributed, as in Table1

Table 4.1 Shapiro-Wilk Test of Normality

Tools	Shapiro-Wilk
	Test value	P-value
Social Intelligence Scale	1.13	0.82
Speaking test	0.93	0.81

        Table (1) shows that the data collected using the research

instruments (SIS, and Speaking test) is normally distributed. In this sense, it is evident that the p-values of both the tools are greater than the test values. So, the p-value of SIS is 0.82, which is greater than 0.05. Similarly, the p-value of the speaking test is 0.81, which is greater than 0.05. Consequently, all the P-values of the data are greater than the value of 0.05. This means that the distribution of the data is normal.

4.1 Hypothesis Number One

The first hypothesis reads that “there is a statistically significant difference between the Iraqi EFL learners’ calculated mean score in a. SI, b. speaking skill, and the hypothetical mean score”. This hypothesis, in fact, involves two minor hypotheses or parts. Therefore, each minor hypothesis or variable is tested separately.

4.1.1 Testing the Subjects’ Level of SI

The first part of hypothesis Number One poses that “there is a statistically significant difference between the Iraqi EFL learners’ calculated mean score in SI and the hypothetical mean score." To find out the subjects’ level of SI, their results collected through distributing the (SIS) which were statistically analyzed using the SPSS program. This program computes the mean and the standard deviation of the results to get a first sight and then tests the significance of this mean using the one-sample t-test to get closer insight. As it is shown in table (.2

Table 2 Results of T-Test regarding the Subjects’  

N	Mean	Test Value	Std. Deviation	T _ test		Sig.
				Cal.	Tab.
77	73.805	50	7.158	29.18	1.994 df. : 76, 0.05

 

 

    The statistical results in table (2) show that the subjects possess a good level of social intelligence. In this regard, the mean score of the SIS results is 73.8052, with a degree of deviation of 7.15806. This mean score is, in fact, greater than the hypothetical one (test value), which is 50. Moreover, the spread or divergence from the central mean score is not that great. To ensure the significance of this mean score, nonetheless, the one-sample t-test is executed. It is found that the calculated T-value is greater than the tabulated one since the former is 29.182 and the latter is 1.994 under 76 degrees of freedom at a 0.05 level of significance. This statistically can be interpreted as a significant mean score. In turn, this indicates that the first minor hypothesis concerning SI is accepted.

4.1.2 Testing the Subjects’ Level of Speaking Skill

The second minor hypothesis states that "there is a statistically significant difference between the Iraqi EFL learners’ calculated mean score in speaking skill and the hypothetical mean score.” To this end, the subjects’ mean score is computed and tested using a one-sample t-test to check for its statistical significance. Table (3) below presents the statistical outcomes obtained.

Table 3 Results of a One-Sample T-Test to Measure

 

N	Mean	Test Value	Std. Deviation	T _ test		Sig.
				Cal.	Tab.
77	15.53	12.5	3.250	8.185	1.994 df. : 76, 0.05

 

Table 3 above demonstrates that the subjects have a moderate level of speaking skill. The computed mean score, in this regard, is 15.5325 with a degree of standard deviation of 3.25085. This mean score of the subjects in the speaking test is greater than the test value or the hypothetical mean score of 12.5. The significance of the mean score is tested using the one-sample t-test. It is found that the calculated t-value is 8.185, while the tabulated T-value is 1.994 under the degree of freedom of 76 at a 0.05 level of significance. It is clear that the calculated T-value is greater than the tabulated. This means that the computed mean score is statistically significant, leading to the conclusion that Iraqi EFL learners have scored a statistically significant mean score concerning speaking skill. Subsequently, the second minor hypothesis is accepted.

The minor hypotheses are both verified and proved to be accepted since there is a statistically significant difference between the calculated mean score and the hypothetical one concerning the two variables (SI and Speaking Skill). Consequently, Hypothesis Number One is accepted. 

4.2 Hypothesis Number Two

The hypothesis reads that “there is a moderate positive correlation between SI and speaking skill.” The subjects' levels in SI and speaking skill was computed and tested for significance. It is found that the subjects exhibit a good level of SI and speaking skill. Based on this result, the correlation between the two variables is computed using the Pearson correlation coefficient. The statistics of this association are presented in table (4).

 

Table 4.The Correlation between SI and Speaking Skill

N	Pearson Correlation	T _ test		Sig.
		Cal.	Tab.
77	0.358	3.320	1.995 df. : 75, 0.05	Sig.

The results in (Table 4) demonstrate that the correlation coefficient between SI and speaking skill is found to be 0.358. This value is then tested using a t-test to determine its statistical significance. In this regard, the calculated T-value is found to be 3.320 at a 0.05 level of significance and 75 degrees of freedom. On the other hand, the tabulated t-value is computed as 1.995. This means, in statistical terms, that the correlation is statistically significant. The strength of this correlation coefficient is estimated as moderate since the R-value is within the range between 3-7. Moreover, the direction of the correlation is observed as a positive one. As a result, the second hypothesis is proved to be accepted.

4.3 Hypothesis Number Three

This hypothesis reads that “There is a statistically significant difference in the correlation between SI and speaking skill according to the personal variables (gender and ethnicity)”.

4.3.1 The Correlation between SI and Speaking Skill Concerning Gender

The influence of gender is taken into account when assessing the correlation between SI and Speaking. The results are presented in table (5).

Table 5 .The Correlation between SI and Speaking Skill According to Gender

 

Ethnicity	N	Correlation	dr.	Z _ test		Sig.
				Cal.	Tab.
Arabs	52	0.363	0.383	0.191	1.96 α: 0.05	N.S.
Kurds	11	0.301	0.310
Arabs	52	0.363	0.383	0.120	1.96 α: 0.05	N.S.
Turkmen	14	0.329	0.343
Kurds	11	0.301	0.310	0.071	1.96 α: 0.05	N.S.
Turkmen	14	0.329	0.343

 

 

 

The results presented in the table show that female subjects scored 0.259, whereas males 6.134. Compared with the standard degrees of correlation, which are 0.266 for females and 0.136 for males, the correlation coefficient seems weak. Female subjects exhibit a relatively greater correlation coefficient than males.  To estimate the influence of the gender distinction on this coefficient of correlation, Z-test is applied. It is found that the calculated z-value is 0.546, while the tabulated one is 1.96 at the level of significance 0.05. The calculated z-value is noticeably less than the tabulated one. Therefore, there is no statistically significance difference due to gender variable in the correlation between SI and speaking skill. Consequently, the first part of the third hypothesis is rejected.

4.3.2 The Correlation between SI and Speaking Skill Concerning Ethnicity

With regard to the impact of ethnicity on the correlation between SI and speaking, the z-test is used to detect any possible significant differences. The results are presented in table (6).

Table 6 The Correlation between SI and Speaking Skill According to Ethnicity

 

Gender	N	Correlation	dr.	Z _ test		Sig.
				Cal.	Tab.
male	36	0.134	0.136	0.546	1.96 α: 0.05	N.S.
female	41	0.259	0.266

 

    The results show that Arab subjects scored a correlation coefficient of 0.363, Kurds 0.301 and Turkmen 0.329. However, when these R-values are compared with their corresponding dr, values, these correlation coefficients appear insignificant because the dr. values are greater than the R-values. It seems that Arab subjects scored a correlation coefficient greater than that of the Kurds and Turkmen. Nonetheless, a closer look, using the z-test reveals that this difference among the variables has no statistical potential. The calculated z-value of the difference between the coefficient of Arabs and Kurds is 0.191, while the tabulated is 1.96. Moreover, the computed z-value of Arabs and Turkmen is 0.120, whereas the tabulated one is 1.96. Additionally, the calculated z-value of Kurds and Turkmen is 0.071, and the tabulated is 1.96, all at a 0.05 significance level. The results of the z-test show that all the calculated values are less than the tabulated ones at the given level of significance. Consequently, this means that there is no statistically significant difference. Judging from the case, it can be said that the ethnicity variable does not impact the correlation between SI and speaking skill in a statistically significant value. Therefore, the second part of the third hypothesis is rejected.

Since both parts of the third hypothesis are rejected, this means that the third hypothesis is rejected and there is no statistically significant effect of personal variables on the correlation between SI and speaking skill at a 0.05 level of significance.

4.4 Discussion of Findings

After analyzing the results and testing the hypotheses, the study identifies several key findings. These findings are concluded depending on the statistical results. It is found that Iraqi EFL learners scored good levels at SI, and Speaking Skill. Moreover, the results reveal that there exists a moderate positive correlation between SI and Speaking Skill. This finding shows that an increase in the learners’ level of SI can cause an increase in their speaking skill. It confirms that having a good level of SI would help to boost learners’ overall communication abilities including speaking. Being socially intelligent and willing to interact with others, means that learners are willing to use the target language effectively and appropriately.

 These findings agree with those of a study carried out by Khodadady and Namaghi (2013) (42) found that there is a significant correlation between SI and language proficiency among Iranian EFL learners. Moreover, a study carried out by Ahmed and Mohammad (2020) (37) concluded that there is a positive association between Yamani EFL learners’ level of SI and their performance in the foreign language. These findings, similar to this study, confirm the fact that SI can impact EFL learners’ level of mastering the target language. In this sense, enhancing the level of SI may play a significant role in increasing students’ levels of mastering the target language.

Shifting to the personal variables, it is found that the effect of gender difference on the correlation between the variables does not significantly influence the association. This means that difference in gender does not grant males or females to be better than the other. A study by Maftoon and Najafi (2015) (43) concluded that difference in gender does not result in a statistically significant difference in favour of one gender over the other. As for the effect of ethnicity distinction, however, on the correlation between the two variables, it showed no statistically significant difference.

5. 5. Conclusions

After shedding light on the theoretical and practical aspects of the variables, the study draws the following conclusions:

1.Social intelligence is not an easy construct to be holistically tested since it covers multiple dimensions within the cognitive and behavioral aspects.

2.The statistical analysis of the study concludes that Iraqi EFL university students demonstrate fairly good level of social intelligence and a moderate level of speaking skill.

3.There is a moderate positive correlation between social intelligence and speaking skill.

4.Gender and ethnicity difference as an external variable do not influence the correlation between SI and speaking skill.

6. 6. Recommendations

The following recommendations are presented:

1.Social intelligence is a multidimensional construct; therefore, it is recommended to use tests that target the cognitive and behavioral aspects of this construct.

2.Teaching materials, such as conversation curricula, should place greater emphasis to activities that boost interpersonal awareness. This would increase learners’ SI. Activities such as role playing, debate, discussion, etc. provide practical and theoretical enhancement of social intelligence and speaking skill. It helps to provide insightful evidence on the way communication better takes place.   

3.Social intelligence is an important attribute in one’s workplace. Therefore, Institutions are recommended to hold educative seminars and training courses to improve their students' SI to prepare them for the next phase of their lives. 

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